import torch

in_channels, out_channels = 5, 10
width, height = 100, 100
kernel_size = (3,3)
batch_size = 1

input = torch.randn(batch_size,
                    in_channels,
                    width,
                    height)

conv_layer = torch.nn.Conv2d(in_channels,
                             out_channels,
                             kernel_size=kernel_size)

out_put = conv_layer(input)

print(input.shape)
print(out_put.shape)
print(conv_layer.weight.shape)
